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  • The AtomOWL ontology is inspired from the work done by the atom working group. This ontology is working off the rfc 4287 published among othe places at http://www.atompub.org/rfc4287.html . The AtomOWL ontology uses as much as possible the same terms as the format there to make the relation easy to understand. The AtomOWL name space is slightly different from the atom namespace [see post http://www.imc.org/atom-syntax/mail-archive/msg16476.html]. But this is a good thing as it helps distinguish the ontology from the rfc 4287 serialisation. @en
  • The euBusinessGraph (`ebg:`) ontology represents companies, type/status/economic classification, addresses, identifiers, company officers (e.g., directors and CEOs), and dataset offerings. It uses `schema:domainIncludes/rangeIncludes` (which are polymorphic) to describe which properties are applicable to a class, rather than `rdfs:domain/range` (which are monomorphic) to prescribe what classes must be applied to each node using a property. We find that this enables more flexible reuse and combination of different ontologies. We reuse the following ontologies and nomenclatures, and extend them where appropriate with classes and properties: - W3C Org, W3C RegOrg (basic company data), - W3C Time (officer membership), - W3C Locn (addresses), - schema.org (domain/rangeIncludes and various properties) - DBpedia ontology (jurisdiction) - NGEO and Spatial (NUTS administrative divisions) - ADMS (identifiers), - FOAF, SIOC (blog posts), - RAMON, SKOS (NACE economic classifications and various nomenclatures), - VOID (dataset descriptions). This is only a reference. See more detail in the [EBG Semantic Model](https://docs.google.com/document/d/1dhMOTlIOC6dOK_jksJRX0CB-GIRoiYY6fWtCnZArUhU/edit) google document, which includes an informative description of classes and properties, gives examples and data provider rules, and provides more schema and instance diagrams. @en
  • The Vocabulary of Dataset Publication Projects (VDPP) allows to represent the status of a dataset publication project. It is mainly based on the Provenance Vocabulary (PRV), the Dataset Provenance Vocabulary (VOIDP), the Vocabulary of Interlinked Datasets (VoID), and the Description of a Project (DOAP) vocabulary. @en
  • A vocabulary to annotate RDF schemas (in particular SHACL shapes) with metadata to define mappings to GraphQL. @en
  • An OWL representation of parts of the Geographic Metadata model described in ISO 19115:2003 with Corrigendum 2006 - DQ Package @en
  • R4R is a light-weight ontology for representing general relationships of resource for publication and reusing. It asserts that a certain reusing context occurred and determined by its two basic relations, namely, isPackagedWith and isCitedBy. The isPackagedWith relation declares the resource is ready to be reused by incorporating License and Provenance information. The Cites relation is an exceptional to isCitedBy which occurs only two related objects cite each other at the same time. Five resource objects including article, data, code, provenance and license are major class concepts to represent in this ontology. The namespace for all R4R terms is http://guava.iis.sinica.edu.tw/r4r/ @en
  • MARC relators are defined as both RDF properties and SKOS concepts @en
  • hRESTS is a vocabulary for describing RESTful Web services @en
  • A simple RDF(S) ontology able to capture (part of) the semantics of both Web services and Web APIs @en
  • The Knowledge Diversity Ontology aims at providing a vocabulary that describes different dimensions of knowledge diversity of the Web. To support the representation of diversity information, the conceptual model of the Knowledge Diversity Ontology includes concepts and relations that were identified and modelled by focusing on real world scenarios in context of customer feedback, news, and Wikipedia opinion mining as well as content and sentiment analysis. @en
  • Endpoint Status vocabulary intends to describe endpoint availability @en
  • The provenance part of PML2 ontology. It is a fundamental component of PML2 ontology. @en
  • Lemon: The lexicon model for ontologies is designed to allow for descriptions of lexical information regarding ontological elements and other RDF resources. Lemon covers mapping of lexical decomposition, phrase structure, syntax, variation, morphology, and lexicon-ontology mapping. @en
  • An ontology for natural language terms description, including scripts, languages and meanings. The Lexvo.org ontology is still under development and may not be able to address all needs. Please also consider using the Lingvoj Ontology and the GOLD ontology, whereever appropriate. @en